Method and apparatus for interactive curve generation

ABSTRACT

A system of curve generation takes a sequence of control points and constraint codes for each control point, and outputs a curve in which each of the constraints is satisfied. The set of constraints is chosen from the tangent angle, curvature, first derivative of curvature, and second derivative of curvature. The interactive curve design uses as its primitive, a curve whose curvature is a polynomial function of arclength (whose intrinsic equation is a polynomial). At each control point, a choice of G2 curvature continuity (tangent angle and curvature) or G4 curvature continuity (tangent angle and curvature plus first and second derivatives of curvature are continuous) is input. The desired curve is expressed as the solution to the chosen set of constraints.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.13/961,984, filed Aug. 8, 2013, which is a continuation of U.S. patentapplication Ser. No. 11/752,260, filed May 22, 2007, which claims thebenefit of U.S. Provisional Application No. 60/747,931, which was filedon May 22, 2006, and U.S. Provisional Application No. 60/915,919, whichwas filed on May 3, 2007. The disclosure of each of the aboveapplications is incorporated herein by reference in its entirety.

FIELD OF THE INVENTION

The present invention relates to interactive curve design.

BACKGROUND OF THE INVENTION

The literature of curve interpolation techniques, otherwise known as“splines” is vast. A system for interactive design of curves should havethe following properties: (a) The system should be capable of accuratelyrepresenting a rich variety of curves with a minimum of input (measuredas the number of control points); (b) The resulting curves should besmooth; (c) When moving control points, the effect on the curve shouldbe direct and simple to understand; and (d) The computational resourcesshould be modest enough to allow for update of the display atinteractive rates. Much curve design, including most font design, isdone using cubic Bezier curves. FIG. 3 shows a typical cubic Beziersegment with knots and additional control points. In a Bezier curve,some of the control points (“knots or knot points”) lie on the curve(30, 36), but others lie off the curve (32, 34), and the position of theoff-curve control points controls the shape of the curve. As thedesigner moves control points 32 and 34, the shape of the curve betweencontrol points 30 and 36 changes. This technique is simple to computeand very fast, and is good at representing a rich diversity of curves,but is not very simple to control. It is especially difficult to achievesmooth curves through the on-curve control points, and it takesconsiderable time and effort for designers to learn to do so. Aparticularly difficult aspect of curve design for font generation ismaking smooth transitions between straight and curved sections.Smoothness is a subjective quality, and there is no consensus in theliterature on the best way to measure it, but one very commonly relatedobjective measure closely connected to smoothness is the degree ofcontinuity across the knot points. This continuity measure, in turn, isdefined in terms of “curvature”. Curvature is defined as the inverse ofinstantaneous radius, i.e., the inverse of the radius of the osculatingcircle that “kisses” the curve at every point. If the curvature existsat all points (i.e. there are no sharp corners), then the curve has G1continuity.

If the curvature is also continuous through the control point, then ithas G2 continuity. Higher degrees of continuity are defined in terms ofderivatives of the curvature with respect to arclength. If the firstderivative of curvature is continuous, then the curve has G3 continuity,and if the second derivative of curvature is also continuous, then thecurve has G4 continuity. In general, cubic Bezier curves only guaranteeG1 continuity. Another class of curve generation techniques involves“interpolating splines,” or curves that go through (“interpolate”) allthe control points. One example used in practice for font design is“Smooth, Easy to Compute Interpolating Splines,” by John Hobby, StanfordUniversity, 1985 as implemented in the METAFONT system. In the prior artMETAFONT spline, the range of choices for constraints is limited (theconstraint is that of continuity of “mock curvature” across controlpoints). In curve design, a primitive is defined as the basic elementupon which more complex curves are built. The underlying primitive curvein the METAFONT system is a reduced family of cubic polynomials (with atwo-dimensional parameter space). Another prior art system known asIkarus, by Peter Karow, is similar to METAFONT.

Yet another class of interpolating spline techniques is the “variationalapproach,” in which a curve is chosen to minimize some energyfunctional. Such techniques emulate mechanical splines based on thinstrips of elastic material such as metal or wood. Examples includeGumhold (Designing Optimal Curves in 2D, Proc. CEIG, July 2004 pages61-76), and Moreton (Minimum Curvature Variation Curves, Networks andSurfaces for Fair Free-Form Shape Design, 1992 University of California,Berkeley Calif.). In general, variational techniques provide for a highdegree of smoothness, but also require substantial computationalresources. Moreton described MEC (Minimum Energy Curve) with G2continuity and also MVC (Minimum Variation of Curvature) splines with G4continuity.

SUMMARY OF THE INVENTION

The invention is a novel technique for interactive curve design,comprising several innovative features. Although the present inventionis illustrated for use in conjunction with font design, the techniquemay be applied railroad track design, roadway design, and general CADapplications involving smooth curves.

In accordance with a first feature, the present invention uses as itsprimitive, a curve whose curvature is a polynomial function ofarclength, i.e. whose intrinsic equation is a polynomial.

In accordance with a second feature, for each control point, the presentinvention allows for a choice of G2 or G4 curvature continuity.

In accordance with a third feature, the present invention provides fortransitions between straight and curved sections, in which G2 continuityis preserved.

In the present system, the desired curve is expressed as the solution toa set of constraints. The set of constraints is chosen from the tangentangle, curvature, first derivative of curvature, and second derivativeof curvature. In summary, the input to the system is a sequence ofcontrol points and constraint codes for each control point, and theoutput is a curve in which each of the constraints is satisfied.

DESCRIPTION OF THE DRAWING

FIG. 1 illustrates the use of the present invention for font generation.

FIG. 2 illustrates the use of the present invention for interactive fontdesign.

FIG. 3 illustrates a method of curve generation in accordance with theprior art.

FIG. 4 is an example of an Euler spiral for use in conjunction with thepresent invention.

FIG. 5 shows a unit-length normalized polynomial spiral segment for usein conjunction with the present invention.

FIG. 6A shows a typical font outline generated using the presentinvention.

FIG. 6B shows a typical font outline generated using the presentinvention, with an Euler spiral overlaying one such segment.

FIG. 7 shows a family of font outlines of varying weight in accordancewith the present invention, produced by linearly interpolating thecontrol points.

FIG. 8 shows the family of font outlines shown in FIG. 7, superimposedto show more clearly the relations between the curves of the differentoutlines.

FIG. 9A shows a font outline for a “U” letter in accordance with thepresent invention.

FIG. 9B is a plot showing curvature as a function of arclength for thefont outline of the “U” letter in FIG. 9A in accordance with the presentinvention.

DETAILED DESCRIPTION OF THE INVENTION

A system using the present invention for document printing isillustrated in FIG. 1. A document 100 includes text 104 and a fontidentifier (font ID) 102. The font ID 102 contains the control points(data points or knots) for each character in the chosen font.

Prior to printing or displaying the document 100, a font generator 106renders each character, which is then stored in a bitmap memory 108. Thepresent invention for curve generation finds its utility in the fontgenerator 106 where the curves between control points are computed.

In order to print (or display) the document 100, individual charactersof the text 104 contained in the document 100 are sent to theprint/display engine 110, which uses the stored bitmap of each characterin memory 108 to render the document 100 on a display 112 or generate aprinter output 114.

An interactive system using the present invention for font design isillustrated in FIG. 2. The font designer provides input 200 in the formof selecting control points 201 that correspond to the shape of thedesired font characters. The control points are sent to the fontgenerator 206.

In accordance with the present invention, the font generator 206computes the curves between the selected control points 201. Theresulting bitmap for such character is stored in a bitmap memory 208. Aprint/display engine 210 generates a display 212 and/or a printed output214 for evaluation by the font designer. The rapid computation of curvesby the font generator 206 on the display 212 permits effectiveinteractive font design. When the font designer is satisfied with theshape of the displayed character, the control points are saved 204 in afont ID memory 202.

The interactive qualities achieved by the use of the present inventionare illustrated in FIG. 7 and FIG. 8. FIG. 7 shows the result using thepresent invention when the control points are linearly interpolatedbetween two versions of a font outline. In particular, FIG. 7 shows athin version 7A of a font linearly interpolated up to a thick version 7Kof the same font. All such instances of the font 7A, 7B . . . , 7J, 7K,have G2 continuity everywhere (other than corners). By contrast,linearly interpolating Bezier control points, as in the Adobe MultipleMaster technology, does not even guarantee G1 continuity in the generalcase.

FIG. 8 illustrates the same linear interpolation between a thin version8A of a font linearly interpolated up to a thick version 8K of the samefont. In particular, FIG. 8 shows a thin version 8A of a font linearlyinterpolated up to a thick version 8K of the same font superimposed uponeach other. All such instances of the font 8A, 8B . . . , 8J, 8K, haveG2 continuity everywhere (other than corners).

The Primitive Curve

The preferred primitive curve of the present invention is a third-orderpolynomial spiral. A polynomial spiral is a curve whose curvatureexpressed in terms of arclength (its “intrinsic equation”) is given by apolynomial. Each such curve is characterized by four scalar parameters,which may be represented as the curvature and its first threederivatives at the midpoint of the curve. A few special cases are worthnoting. If all four parameters are zero, then the curve is a straightline. If the curvature is nonzero but its derivatives are zero, then thecurve is a circular arc of constant curvature. If the first twoparameters are nonzero and the second and third derivatives of curvatureare zero, then the curve is a clothoid, or a segment of the spiral ofCornu. Polynomial spirals are also known as “generalized clothoids”.

The Constraints

Since each segment is a determined by four parameters, in a closed curveeach point must have exactly four scalar constraints, to make sure thatthe resulting curve is fully determined.

A G4 constraint specifies that the tangent angle, curvature, firstderivative of curvature, and second derivative of curvature must beequal across the control point.

A G2 constraint specifies that the tangent angle and curvature must beequal across the control point. To satisfy the requirement that eachcontrol point has a total of four scalar constraints, we add twoadditional constraints: the second derivative of curvature must be zeroon both sides of the control point.

A one-way constraint with the straight side on the left and the curvedside on the right is as follows. As in a G2 constraint, tangent angleand curvature must be equal across the control point. On the left(straight side), both first and second derivative of curvature must bezero.

The palette of constraints contains eight possible choices, namely thetangent angle, curvature, first derivative of curvature, and secondderivative of curvature on one side of the control point, and thetangent angle, curvature, first derivative of curvature, and secondderivative of curvature on the other side of the control point. Ingeneral, constraints at each control point can be written in terms of alinear combination of these eight possible parameters set equal to aconstant (typically zero). Any set of four of these constraints is avalid set of constraints.

In an open curve, there is one more point than the number of segments,so the endpoints are treated specially. Each endpoint is assigned twoconstraints, specifically that the first and second derivatives ofcurvature are zero. In this way, the total number of constraints isalways four times the number of segments, as required.

These constraints can be mixed freely and at will. The resulting curve,after solution of the spline, has a number of notable properties.

First, any segment bounded by a standard G2 constraint on both ends is asegment of an Euler spiral, also known as clothoid. A spline consistingentirely of G2 constraints is known as an Euler spiral spline. Euler'sspiral, plotted in FIG. 4 over the range [−5, 5], is characterized byits intrinsic definition: curvature is linear with arclength, namely,k(s)=s/2.

Second, if all points have G4 control points, the spline described byOhlin in “Splines for Engineers.” spline is generated.

Third, if points are perturbed on the curved side of a one-wayconstraint, the curve on the straight side is not affected. In additionto providing for smooth straight-to-curved transitions, this propertyallows the construction of curves more robust with respect toperturbation, as may be useful when the control points themselves areparameterized or interpolated.

Implementation of the Constraint Solver

The core of the preferred embodiment of the present invention is aconstraint solver specialized to the particular systems of constraintsthat will be solved: a sequence of segments each of which is apolynomial spiral controlled by four parameters, and an equal number ofconstraints written in terms of the tangent angles, curvatures, andderivatives of curvature at the endpoints of each of the segments.

In broad outline, the solver works as follows:

-   -   1. Determine initial values for all the parameters. One        reasonable choice is all zeros, so that initially the segments        are straight lines. The result of this step can be represented        as a vector.    -   2. Evaluate the tangent angles, curvatures, and derivatives of        curvature at the endpoints of each of the segments.    -   3. For each constraint, evaluate a quantity that represents the        deviation from the constraint. For constraints of the form        “quantity equals zero”, this deviation is the quantity itself.        For constraints of the form “first quantity=second quantity”,        this deviation is the difference between the two quantities,        i.e. “first quantity minus second quantity”. The result of this        step is a vector of deviation values.    -   4. Determine whether the deviation vector is within an        acceptable tolerance of zero. If it is exactly zero, then the        constraints are exactly satisfied. If it is close to zero, then        the constraints are approximately satisfied.    -   5. If the deviation vector is within tolerance, then the solver        is complete, and the result is the vector of parameters.    -   6. For each combination of parameter value and deviation value,        compute an approximate value of how an infinitesimal change to        the parameter will affect the deviation. The result of this step        is a matrix. Further, this matrix is sparse and can be        represented in band-diagonal form because changes to parameters        only affect the deviations at the left and right endpoints.    -   7. Invert the matrix generated in step 6, above. While inversion        of arbitrary matrices is fairly expensive computationally,        efficient algorithms exist for inverting matrices in        band-diagonal form. See Numerical Recipes in C, 2^(nd) ed. by        William H. Press, Brian P. Flannery, Saul A. Teukolsky,        William T. Vetterling. Cambridge University Press, 1992.    -   8. Compute the dot product of the inverted matrix and the        deviation vector, resulting in an update vector.    -   9. Subtract the update vector from the parameter vector,        resulting in a refined parameter vector.    -   10. G0 back to step 2 and repeat the process.

Evaluation of Tangent Angles, Curvatures, and Derivatives of Curvature

A central sub-problem of the constraint solver (step 2 of the abovesection) is to evaluate the tangent angles, curvatures, and derivativesat each of the two endpoints (control points) of each polynomial spiralsegment, given the four parameters of the polynomial spiral.

The standard representation of a third-order polynomial spiral segmentis as a vector of four quantities measured at the arclength midpoint ofthe segment normalized to unit length: curvature, and the first threederivatives of curvature. By convention, the midpoint has Cartesiancoordinates at the origin (0,0), and has a tangent angle of zero, i.e.parallel to the horizontal axis. FIG. 5 shows an example of such asegment 50 between a first and second endpoints 52, 54.

Using a Taylor's series expansion, the curvature of segment 50 measuredat arclength s from this central point, (i.e. s ranges from −0.5 to0.5), is:

k(s)=k0+k1s+½k2ŝ2+⅙k3ŝ3

The tangent angle at each point along the curve 50, measured in terms ofthe arclength parameter s, can be determined by simple integration ofthis curvature value:

theta(s)=k0s+½k1ŝ2+⅙k2ŝ3+ 1/24k3ŝ4

The Cartesian coordinates of each point along the curve 50, measured interms of the arclength parameter s, can be determined by numericalintegration of the sine and cosine of the tangent angle.

x(s)=integral (from 0) (to s)cos theta(t)dt

y(s)=integral (from 0) (to s)sin theta(t)dt

The chordlength of this segment, which is equal to the ratio ofchordlength divided by arclength because the arclength is unity, issimply the Pythagorean distance between the two endpoints, representedin Cartesian coordinates as (x(−0.5), y(−0.5)) and (x(0.5), y(0.5)),respectively. Thus, this value issqrt((y(0.5)−y(−0.5))̂2+((x(0.5)−x(−0.5))̂2)). The unit-length normalizedsegment is then rotated and scaled so that its endpoints match thecontrol points given as input to the constraint solving problem. Thescale factor is equal to the chordlength between the control pointsdivided by the chordlength of the unit-length normalized segment.

Similarly, the rotation angle is equal to the angle of the vector fromthe left control point to the right control point, minus the angle ofthe vector from the left endpoint to the right endpoint of theunit-length normalized segment (the latter angle is marked by the Greekletter psi in FIG. 5).

With these values (the scale factor and rotation angle), the tangentangles, curvatures, and derivatives can be readily calculated for allpoints along the curve, including the two endpoints.

${{tangent}\mspace{14mu} {{angle}(s)}} = {{( {{rotation}\mspace{14mu} {angle}} ) + {{theta}(s)}} = {( {{rotation}\mspace{14mu} {angle}} ) + {k\; 0\mspace{14mu} s} + {{1/2}\mspace{14mu} k\; 1\mspace{14mu} {s\hat{}2}} + {{1/6}\mspace{14mu} k\; 2\mspace{14mu} {s\hat{}3}} + {{1/24}\mspace{14mu} k\; 3\mspace{14mu} {s\hat{}4}}}}$${{curvature}(s)} = {{{k(s)}/( {{scale}\mspace{14mu} {factor}} )} = {( {{k\; 0} + {k\; 1\mspace{14mu} s} + {{1/2}\mspace{14mu} k\; 2\mspace{14mu} {s\hat{}2}} + {{1/6}\mspace{14mu} k\; 3\mspace{14mu} {s\hat{}3}}} )/( {{scale}\mspace{14mu} {factor}} )}}$${{curvature}^{\prime}(s)} = {{{k^{\prime}(s)}/{( {{scale}\mspace{14mu} {factor}} )\hat{}2}} = {( {{k\; 1} + {k\; 2\mspace{14mu} s} + {{1/2}\mspace{14mu} k\; 3\mspace{14mu} {s\hat{}2}}} )/{( {{scale}\mspace{14mu} {factor}} )\hat{}2}}}$${{curvature}^{''}(s)} = {{{k^{\prime}(s)}/{( {{scale}\mspace{14mu} {factor}} )\hat{}3}} = {( {{k\; 2} + {k\; 3\mspace{14mu} s}} )/{( {{scale}\mspace{14mu} {factor}} )\hat{}3}}}$

These four formulae are then evaluated at s=−0.5 and s=0.5, resulting inthe values for the left and right endpoint, respectively.

FIG. 6A illustrates an “a” letter 64 generated for a typical fontoutline. Although the curve generation in accordance with the presentinvention determines only the outline of the “a” letter 64, it will beunderstood that when printing and displaying the letter outline 64, theinterior of the curve will be a solid color (typically black).

The control points such as 60, 61, 62 and 63 in FIG. 6A identify thefont outline. In accordance with the present invention, a portion of aEuler spiral 640 is fitted between control points 60 and 63 in FIG. 6B.The power of the present invented algorithm for fitting curves betweencontrol points is illustrated by the fact that a single Euler spiral 640passes through all four control points 60, 61, 62 and 63.

FIG. 9A illustrates a font outline for an asymmetrical “U” letter 90.The plot in FIG. 9B shows curvature as a function of arclength for thefont outline of the “U” letter 90 in FIG. 9A.

The peak curvature points 92, 94, 96, 98 correspond to the correspondingcurve segments 92, 94, 96, 98 in FIG. 9A. In between, the short straightsections 93 and 97 in FIG. 9A correspond to the zero curvature segments93 and 97 in FIG. 9B. Similarly, the large curved section 91 and thesmall curved section 95 in FIG. 9A correspond to the positive curvature91 and negative curvature 95 in FIG. 9B. Note the smooth transitionsbetween straight sections (such as segment 99) and curve segments (suchas segment 92).

What is claimed is:
 1. A computer-implemented method, comprising:obtaining, at a computing device, an initial vector of parameter valuesthat defines a curve comprising a plurality of segments, each segment ofthe plurality of segments being defined by four scalar parameters andextending between two endpoints; and determining, at the computingdevice, a final vector of parameter values for the curve, whereindetermining the final vector of parameter values comprises utilizing aniterative process to analyze whether a set of constraints are met ateach endpoint, the iterative process including: (i) analyzing a currentvector of parameter values to determine a vector of deviation valuesbased on deviation from the set of constraints for each endpoint, (ii)determining whether the vector of deviation values is within atolerance, (iii) when the vector of deviation values is within thetolerance, setting the current vector of parameter values as the finalvector of parameter values, and (iv) when the vector of deviation valuesis not within the tolerance: (a) computing a change matrix based on howa change to the current vector of parameters will change the vector ofdeviation values, (b) inverting the change matrix to obtain an invertedchange matrix, (c) obtaining an update vector by computing a dot productof the inverted change matrix and the vector of deviation values, (d)obtaining a refined vector of parameter values by subtracting the updatevector from the current vector of parameter values, and (e) setting therefined vector of parameter values as the current vector of parametervalues to be analyzed.
 2. The computer-implemented method of claim 1,wherein the four scalar parameters are curvature, first derivative ofcurvature, second derivative of curvature, and third derivative ofcurvature at a midpoint of each segment.
 3. The computer-implementedmethod of claim 1, further comprising outputting, from the computerdevice, the final vector of parameter values for the curve.
 4. Thecomputer-implemented method of claim 1, wherein computing the changematrix based on how the change to the current vector of parameters willchange the vector of deviation values comprises computing the changematrix based on how an infinitesimal change to the current vector ofparameters will change the vector of deviation values.
 5. Thecomputer-implemented method of claim 1, wherein the set of constraintscomprises at least one of tangent angle, curvature, first derivative ofcurvature, and second derivative of curvature.
 6. Thecomputer-implemented method of claim 5, wherein the set of constraintsspecifies that the tangent angle, curvature, first derivative ofcurvature, and second derivative of curvature are equal across eachendpoint.
 7. The computer-implemented method of claim 5, wherein the setof constraints specifies that: (i) the tangent angle and curvature areequal across each endpoint, and (ii) the second derivative of curvatureis zero on both sides of each endpoint.
 8. The computer-implementedmethod of claim 5, wherein the set of constraints specifies that: (i)the tangent angle and curvature are equal across each endpoint, and (ii)both the first and second derivatives of curvature are zero on one sideof each endpoint.
 9. The computer-implemented method of claim 8, whereina first segment on a first side of a specific endpoint is a straightline and a second segment on a second side opposite the first side ofthe specific endpoint is a curved segment.
 10. The computer-implementedmethod of claim 1, wherein each specific segment of the plurality ofsegments has a curvature and an arclength at each point along thespecific segment, the curvature at each specific point of the specificsegment being a polynomial function of the arclength corresponding tothat specific point.
 11. The computer-implemented method of claim 1,further comprising: generating, at the computing device, the curve basedon the final vector of parameter values; and outputting, from thecomputer device, the curve to a display device or printer.
 12. Acomputer-implemented method, comprising: obtaining, at a computingdevice, an initial vector of parameter values that defines a curvecomprising a plurality of segments, each segment of the plurality ofsegments being defined by four scalar parameters and extending betweentwo endpoints; and determining, at the computing device, a final vectorof parameter values for the curve, wherein determining the final vectorof parameter values comprises utilizing an iterative process to analyzewhether a set of constraints are met at each endpoint, the iterativeprocess including: (i) analyzing a current vector of parameter values todetermine a vector of deviation values based on deviation from the setof constraints for each endpoint, (ii) determining whether the vector ofdeviation values is within a tolerance, (iii) when the vector ofdeviation values is within the tolerance, setting the current vector ofparameter values as the final vector of parameter values, and (iv) whenthe vector of deviation values is not within the tolerance, obtaining arefined vector of parameter values by modifying the current vector ofparameter values and setting the refined vector of parameter values asthe current vector of parameter values to be analyzed.
 13. Thecomputer-implemented method of claim 12, wherein the set of constraintscomprises at least one of tangent angle, curvature, first derivative ofcurvature, and second derivative of curvature.
 14. Thecomputer-implemented method of claim 13, wherein the set of constraintsspecifies that: (i) the tangent angle and curvature are equal acrosseach endpoint, and (ii) the second derivative of curvature is zero onboth sides of each endpoint.
 15. A method for solving curvatureconstraints for a sequence of polynomial spiral segments, said methodcomprising: selecting four scalar parameters for a curve whose curvatureis a polynomial function of arclength; means for computing a set ofconstraints at the controls points at each of the segments, comprisingof tangent angles, curvatures, and first and second derivatives ofcurvature; computing a vector of deviation values for each constraint;and generating a vector of parameters values if the said vector ofdeviation values is within tolerance.
 16. The method of claim 15,further comprising: generating an inverted matrix measuring how aninfinitesimal change to said vector parameter values will affect thesaid vector of deviation values; generating an update vector on the dotproduct between said inverted matrix and said vector of deviationvalues; and generating a refined parameter vector by subtracting saidupdate vector from said vector of parameters values.
 17. The method asin claim 15, wherein a constraint from said set of constraints specifiesthat the tangent angle, curvature, and first and second derivative ofthe curvature must be equal across a said control point.
 18. The methodas in claim 15, wherein a constraint from said set of constraintsspecifies that the tangent angle and curvature must be equal across saidcontrol point, and the second derivative of curvature must be zero onboth sides of a said control point.
 19. The method as in claim 15,wherein a constraint from said set of constraints specifies that thetangent angle and curvature must be equal across said control point, andboth the first and second derivative of curvature must be zero on oneside of said control point.
 20. The method of claim 19, wherein thesegment on one side of a said control point is a straight line and thesegment on the second side of said control point is a curved segment.